call

A task specification for a pool of another language’s workers.

Usage

Source

call(
    name=None,
    /,
    *args,
    source=None,
    **kwargs,
)

Describes a call for Pool.submit(): a qualified name ("mod.fn" for Python workers, "pkg::fn" for R workers) or a source= string in the workers’ language, plus the constant arguments. The spec describes a call; it is not a value. The language never appears at the call site — Pool.submit resolves the workers’ language from the pool itself — and a bare (unqualified) name errors at submit, not here.

Parameters

name: str | None = None

A qualified name: "mod.fn" for Python workers, "pkg::fn" for R workers.

args: _Any = ()

Constant positional arguments of the call.

source: str | None = None

A source string in the workers’ language. Exactly one of name or source must be given.

kwargs: _Any = {}

Constant keyword arguments of the call.

Details

Unnamed arguments map to the positional list and keyword arguments to the named dict, matching R’s mixed-call convention. Arguments must be portable values (the interchange subset documented under Channel.send()): a non-portable argument raises DeclinedError at submit, never a fallback.

A source= task evaluates in a fresh namespace with the keyword arguments bound as names and positional arguments bound as _1, _2, … The result is the trailing expression’s value, or None when the source ends with a statement.

Large arguments cross to foreign workers by reference rather than by copy: one fresh buffer argument past the zero-copy floor stages a single layout write into a shared region (the worker reads a view over it), and an argument that is already a shared view crosses as its identifier alone — zero payload bytes. On a pool whose workers predate the ref reader, such a task declines locally at submit naming the remedy.

Examples

A spec task also runs on a normal (Python-worker) pool:

>>> import pymizu
>>> with pymizu.Pool.create(2) as pool:
...     task = pool.submit(pymizu.call("math.sqrt", 2.0))
...     results = pool.collect_all([task], timeout=10)
>>> results
[1.4142135623730951]